nateraw/codellama-13b-instruct 🔢📝 → 📝

▶️ 13 runs 📅 Sep 2023 ⚙️ Cog 0.8.6
code-generation code-understanding question-answering text-generation

Example Output

Output

Here is an example of a Python function that reads an HTML file from the internet and extracts the text content of all the h1 elements:

import requests
from bs4 import BeautifulSoup

def get_h1_text(url):
   response = requests.get(url)
   soup = BeautifulSoup(response.content, 'html.parser')
   h1_elements = soup.find_all('h1')
   h1_text = []
   for h1 in h1_elements:
       h1_text.append(h1.text.strip())
   return h1_text

This function uses the requests library to make an HTTP GET request to the specified URL, and the BeautifulSoup library to parse the HTML response. The function then uses the find_all() method of the BeautifulSoup object to find all the h1 elements in the HTML document, and appends the text content of each h1 element to a list called h1_text. Finally, the function returns the h1_text list.

Here is an example of how you could use this function:

url = 'https://www.example.com'
h1_text = get_h1_text(url)
print(h1_text)

This would print a list of all the text content of the h1 elements in the HTML document at the specified URL.

Performance Metrics

43.38s Prediction Time
151.29s Total Time
All Input Parameters
{
  "top_k": 50,
  "top_p": 0.95,
  "message": "Write a python function that reads an html file from the internet and extracts the text content of all the h1 elements",
  "temperature": 0.8,
  "system_prompt": "Provide answers in Python",
  "max_new_tokens": 1024
}
Input Parameters
top_k Type: integerDefault: 50
The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering).
top_p Type: numberDefault: 0.9
A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751).
message (required) Type: string
temperature Type: numberDefault: 0.2
The value used to modulate the next token probabilities.
system_prompt Type: stringDefault: Provide answers in Python
The system prompt to use (for chat/instruct models only)
max_new_tokens Type: integerDefault: 256
The maximum number of tokens the model should generate as output.
Output Schema

Output

Type: arrayItems Type: string

Example Execution Logs
Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.
Version Details
Version ID
4d4dfb567b910309c9501d56807864fc069ffcd2867552aea073c4b374eef309
Version Created
September 28, 2023
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